Special Effects, Machine Learning, and You...
I'm not really a graphics person so much as I'm a Hollywood special effects person.
These days my work on special effects focuses quite a bit on face and body animation and simulation, trying to outwit the uncanny valley.
Traditionally, one used only computer vision techniques for this sort of work, but we're now successfully mixing in quite a bit of physical simulation too.
In fact, I have many ongoing projects mixing in real world data and simulation in order to create more realistic simulations for Hollywood special effects.

It turns out that students interested in Hollywood special effects with backgrounds in math, physics, computer vision, and machine learning (all combined) are hard to find.

Brief Bio
Fedkiw received his Ph.D. in Mathematics from UCLA in 1996 and did postdoctoral studies both at UCLA in Mathematics and at Caltech in Aeronautics before joining the Stanford Computer Science Department. He was awarded an Academy Award from The Academy of Motion Picture Arts and Sciences (twice: 2008 and 2015), the National Academy of Science Award for Initiatives in Research,
a Packard Foundation Fellowship, a Presidential Early Career Award for Scientists and Engineers (PECASE), a Sloan Research Fellowship,
the ACM Siggraph Significant New Researcher Award,
an Office of Naval Research Young Investigator Program Award (ONR YIP), the Okawa Foundation Research Grant, the Robert Bosch Faculty Scholarship, the Robert N. Noyce Family Faculty Scholarship, two distinguished teaching awards, etc.
Currently he is on the editorial board of the Journal of Computational Physics,
and he participates in the reviewing process of a number of journals and funding agencies.
He has published about 120 research papers in computational physics, computer graphics and vision, as well as a book on level set methods - and is listed on ISIHighlyCited.
Since joining Stanford, he has graduated 30 Ph.D. students.
For the past 17 years, he has been a consultant with Industrial Light + Magic. He received screen credits for his work on "Terminator 3: Rise of the Machines", "Star Wars: Episode III - Revenge of the Sith", "Poseidon", "Evan Almighty", and most recently on "Kong: Skull Island".
Most recently, he has become quite interested in omniscient technology - hardware/sensors both wearable
and throughout the environment - and has co-founded a sapling company PIVOT
to better focus on its potential everyday use.

Research
My research is focused on the design of new computational algorithms for a variety of applications including computational
fluid dynamics and solid mechanics, computer graphics, computer vision and computational biomechanics.

Animations of thin shells with non-flat rest angles (with Robert Bridson). The hollow Buddha on the left uses a weak bending model
and collapses similar to a deflated balloon. In the animation on the right, this is compared to a Buddha with stronger bending forces
that retains its shape similar to a water bottle.

Animations of cloth (with Robert Bridson and John Anderson).

Animations of water (with Doug Enright and Steve Marschner).

MANTASUIT
The goal is to design an underwater diving suit that provides a diver with an exoskeleton for enhanced locomotion,
as well as augmented reality enhancements for underwater vision and directional sound detection.
Concept art by Wilson Tang.

Intel Equipment Donation
- We would like to thank Intel for a recent donation of both processors and related funds that has allowed us to build a cluster with many hundreds of processor cores enabling a great deal of our recent work. In fact, a large fraction of our work over the past decade plus has already been enabled by Intel processors.

We are making certain aspects of our Physics Based Modeling code (PhysBAM) available here on this web site.

A Note on Rejected Papers

All too often young researchers get discouraged when they receive peer reviews that are incorrect, misinformed, or all too often merely intended to silence the authors and their ideas.
Personally, I have always been amazed that academics who devote their lives to producing new information actually work to censure and diminish the work produced by others,
and often take pride in doing just that. As time goes on, one learns to distinguish between those in academia who love the work and those that have instead turned academia
into some sort of career aggressively optimizing their stature at the expense of the community as a whole. For young researchers this can be quite daunting, but I strongly
encourage you to stick to your ideas and goals and the pursuit of what interests you. Remember, the content of your paper and the value of its ideas are not diminished because it
was rejected from your preferred venue. The content of the paper itself does not change because of the name of the journal printed on the upper corner of the page!
To emphasize this, I decided to list my 3 most cited REJECTED papers along with their google scholar citation counts:

"Simulation of Clothing with Folds and Wrinkles", 474 citations, rejected from Siggraph

"Fast Surface Reconstruction using the Level Set Method", 442 citations, rejected from Siggraph

Teaching

Winter quarter 2017 - CS 248 - Interactive Computer Graphics

This is the second course in the computer graphics sequence, and as such it assumes a strong familiarity with rendering and image creation. The course has a strong focus on computational geometry, animation, and simulation. Topics include splines, implicit surfaces, geometric modeling, collision detection, animation curves, particle systems and crowds, character animation, articulation, skinning, motion capture and editing, rigid and deformable bodies, and fluid simulation. As a final project, students implement an interactive video game utilizing various concepts covered in the class. Games may be designed on mobile devices, in a client/server/browser environment, or on a standard personal computer. Prerequisites: CS148.

This is the introductory prerequisite course in the computer graphics sequence which introduces students to the technical concepts behind creating synthetic computer generated images.
The beginning of the course focuses on using OpenGL to create visual imagery, as well as an understanding of the underlying mathematical concepts including triangles, normals, interpolation, texture mapping, bump mapping, etc.
Then we move on to a more fundamental understanding of light and color, as well as how it impacts computer displays and printers.
From this we discuss more thoroughly how light interacts with the environment, and we construct engineering models such as the BRDF and discuss various simplifications into more basic lighting and shading models.
Finally, we discuss ray tracing technology for creating virtual images, while drawing parallels between ray tracers and real world cameras in order to illustrate various concepts.
Anti-aliasing and acceleration structures are also discussed.
The final class mini-project consists of building out a ray tracer to create visually compelling images.
Starter codes and code bits will be provided here and there to aid in development, but this class focuses on what you can do with the code as opposed to what the code itself looks like.
Therefore grading is weighted towards in person "demos" of the code in action - creativity and the production of impressive visual imagery are highly encouraged.
Prerequisites: CS 107, MATH 51.

Although the cell phone started out merely as a portable phone, it has become much more including a portable albeit limited computer that can handle email, games, etc. This class will focus on something else that cell phones have become. They are the first prevalent wearable sensors that gather information about you such as your physical location, whether the phone is being held in an upright position, how fast you might accelerate in motion, etc. This information can be used to help you in your everyday life, but it can also be used for marketing, sales, or to track whether or not you may be at home for the sake of committing a home invasion robbery. In this class we will explore this rapidly advancing field including the current state of technology, what could be accomplished in the near future, sociological and privacy implications, potential governmental regulation, etc. We will also address issues surrounding some of the other instances of this omniscient "big brother" technology in our everyday lives including radar guns used by law enforcement and the recording devices that led to the Watergate scandal. Students will be expected to gather and compile information on various subjects and come to class ready to discuss and debate formulated opinions on the topics.